Other Optimizer Options

default_statistics_target

Parameter description: Specifies the default statistics target for table columns without a column-specific target set via ALTER TABLE SET STATISTICS. If this parameter is set to a positive number, it indicates the number of samples of statistics information. If this parameter is set to a negative number, percentage is used to set the statistic target. The negative number converts to its corresponding percentage, for example, –5 means 5%. During sampling, a random sample size is determined by multiplying the default_statistics_target by 300. For example, if the default value is 100, then 30,000 pages will be randomly read and 30,000 data records will be randomly selected from them to complete the random sampling.

Type: USERSET

Value range: an integer ranging from –100 to 10000

• A larger positive number than the parameter value increases the time required to do ANALYZE, but might improve the quality of the optimizer's estimates.
• Changing settings of this parameter may result in performance deterioration. If query performance deteriorates, you can:
  1. Restore to the default statistics.
  2. Use hints to optimize the query plan.
• If this parameter is set to a negative value, the number of samples is greater than or equal to 2% of the total data volume, and the number of records in user tables is less than 1.6 million, the time taken by running ANALYZE will be longer than when this parameter uses its default value.
• AUTOANALYZE does not allow you to set a sampling size for temporary table sampling. Its default value will be used for sampling.
• If statistics are forcibly calculated based on memory, the sampling size is limited by the maintenance_work_mem parameter.

Default value: 100

random_function_version

Parameter description: Specifies the random function version selected by ANALYZE during data sampling. This feature is supported only in 8.1.2 or later.

Type: USERSET

Value range: enumerated values

• The value 0 indicates that the random function provided by the C standard library is used.
• The value 1 indicates that the optimized and enhanced random function is used.

Default value:

• If the current cluster is upgraded from an earlier version to 8.2.0.100, the default value is 0 to ensure forward compatibility.
• If the cluster version 8.2.0.100 is newly installed, the default value is 1.

constraint_exclusion

Parameter description: Controls the query optimizer's use of table constraints to optimize queries.

Type: USERSET

Value range: enumerated values

• on indicates the constraints for all tables are examined.
• off: No constraints are examined.
• partition indicates that only constraints for inherited child tables and UNION ALL subqueries are examined.
  

  When constraint_exclusion is set to on, the optimizer compares query conditions with the table's CHECK constraints, and omits scanning tables for which the conditions contradict the constraints.

Default value: partition

Currently, this parameter is set to on by default to partition tables. If this parameter is set to on, extra planning is imposed on simple queries, which has no benefits. If you have no partitioned tables, set it to off.

cursor_tuple_fraction

Parameter description: Specifies the optimizer's estimated fraction of a cursor's rows that are retrieved.

Type: USERSET

Value range: a floating point number ranging from 0.0 to 1.0

Smaller values than the default value bias the optimizer towards using fast start plans for cursors, which will retrieve the first few rows quickly while perhaps taking a long time to fetch all rows. Larger values put more emphasis on the total estimated time. At the maximum setting of 1.0, cursors are planned exactly like regular queries, considering only the total estimated time and how soon the first rows might be delivered.

Default value: 0.1

from_collapse_limit

Parameter description: Specifies whether the optimizer merges sub-queries into upper queries based on the resulting FROM list. The optimizer merges sub-queries into upper queries if the resulting FROM list would have no more than this many items.

Type: USERSET

Value range: an integer ranging from 1 to INT_MAX

Smaller values reduce planning time but may lead to inferior execution plans.

Default value: 8

join_collapse_limit

Parameter description: Specifies whether the optimizer rewrites JOIN constructs (except FULL JOIN) into lists of FROM items based on the number of the items in the result list.

Type: USERSET

Value range: an integer ranging from 1 to INT_MAX

• Setting this parameter to 1 prevents join reordering. As a result, the join order specified in the query will be the actual order in which the relations are joined. The query optimizer does not always choose the optimal join order. Therefore, advanced users can temporarily set this variable to 1, and then specify the join order they desire explicitly.
• Smaller values reduce planning time but lead to inferior execution plans.

Default value: 8

enable_from_collapse_hint

Parameter description: Specifies whether to rewrite the FROM list to make the hint take effect, and then rewrite it again based on the from_collapse_limit and join_collapse_limit parameters. This parameter is supported by clusters of version 8.2.0 or later.

Type: USERSET

Value range: Boolean

• on indicates that the FROM list is first rewritten in hint mode.
• off indicates that the FROM list is rewritten without difference.

• If this parameter is enabled, the optimizer preferentially rewrites the FROM list in hint mode. However, you can learn whether a hint takes effect only after the plan is generated.
• If this parameter is disabled, the plan is generated in the same way as that in versions earlier than 8.2.0. That is, the plan is generated regardless of whether the table has hints.

Default value: on

plan_mode_seed

Parameter description: This is a commissioning parameter. Currently, it supports only OPTIMIZE_PLAN and RANDOM_PLAN. OPTIMIZE_PLAN indicates the optimal plan, the cost of which is estimated using the dynamic planning algorithm, and its value is 0. RANDOM_PLAN indicates the plan that is randomly generated. If plan_mode_seed is set to –1, you do not need to specify the value of the seed identifier. Instead, the optimizer generates a random integer ranging from 1 to 2147483647, and then generates a random execution plan based on this random number. If plan_mode_seed is set to an integer ranging from 1 to 2147483647, you need to specify the value of the seed identifier, and the optimizer generates a random execution plan based on the seed value.

Type: USERSET

Value range: an integer ranging from –1 to 2147483647

Default value: 0

• If plan_mode_seed is set to RANDOM_PLAN, the optimizer generates different random execution plans, which may not be the optimal. Therefore, to guarantee the query performance, the default value 0 is recommended during upgrade, scale-out, scale-in, and O&M.
• If this parameter is not set to 0, the specified hint will not be used.

enable_hdfs_predicate_pushdown

Parameter description: Specifies whether the function of pushing down predicates the native data layer is enabled.

Type: SUSET

Value range: Boolean

• on indicates this function is enabled.
• off indicates this function is disabled.

Default value: on

windowagg_pushdown_enhancement

Parameter description: Specifies whether to enable enhanced predicate pushdown for window functions in aggregation scenarios. (This parameter is supported only by clusters of version 8.2.0 or later.)

Type: SUSET

Value range: Boolean

• on indicates that the predicate pushdown enhancement for window functions is enabled in aggregation scenarios.
• off indicates that the predicate pushdown enhancement for window functions is disabled in aggregation scenarios.

Default value: on

implied_quality_optmode

Parameter description: Specifies how to pass conditions for the equivalent columns in a statement. (This parameter is supported only by clusters of version 8.2.0 or later.)

Type: SUSET

Value range: enumerated values

• normal indicates forward compatibility with 8.1.3 and earlier versions, that is, the implied expression behavior is optimized.
• negative indicates that the implied expression behavior is not optimized.
• positive indicates that type conversion expressions are optimized in addition to the operations specified by normal.

Default value: normal

enable_random_datanode

Parameter description: Specifies whether the function that random query about DNs in the replication table is enabled. A complete data table is stored on each DN for random retrieval to release the pressure on nodes.

Type: USERSET

Value range: Boolean

• on: This function is enabled.
• off: This function is disabled.

Default value: on

hashagg_table_size

Parameter description: Specifies the hash table size during HASH AGG execution.

Type: USERSET

Value range: an integer ranging from 0 to INT_MAX/2

Default value: 0

enable_codegen

Parameter description: Specifies whether code optimization can be enabled. Currently, the code optimization uses the LLVM optimization.

Type: USERSET

Value range: Boolean

• on indicates code optimization can be enabled.
• off indicates code optimization cannot be enabled.
  

  Currently, the LLVM optimization only supports the vectorized executor and SQL on Hadoop features. You are advised to set this parameter to off in other cases.

Default value: on

codegen_strategy

Parameter description: Specifies the codegen optimization strategy that is used when an expression is converted to codegen-based.

Type: USERSET

Value range: enumerated values

• partial indicates that you can still call the LLVM dynamic optimization strategy using the codegen framework of an expression even if functions that are not codegen-based exist in the expression.
• pure indicates that the LLVM dynamic optimization strategy can be called only when all functions in an expression can be codegen-based.
  

  In the scenario where query performance reduces after the codegen function is enabled, you can set this parameter to pure. In other scenarios, do not change the default value partial of this parameter.

Default value: partial

enable_codegen_print

Parameter description: Specifies whether the LLVM IR function can be printed in logs.

Type: USERSET

Value range: Boolean

• on indicates that the LLVM IR function can be printed in logs.
• off indicates that the LLVM IR function cannot be printed in logs.

Default value: off

codegen_cost_threshold

Parameter description: The LLVM compilation takes some time to generate executable machine code. Therefore, LLVM compilation is beneficial only when the actual execution cost is more than the sum of the code required for generating machine code and the optimized execution cost. This parameter specifies a threshold. If the estimated execution cost exceeds the threshold, LLVM optimization is performed.

Type: USERSET

Value range: an integer ranging from 0 to INT_MAX

Default value: 10000

llvm_compile_expr_limit

Parameter description: Specifies the limit for compiling expressions with LLVM. If there are more expressions than the limit, only the first ones are compiled and an alarm is generated. (To allow the alarm to be generated, execute SET analysis_options="on(LLVM_COMPILE)" before explain performance is executed.)

Type: USERSET

Value range: an integer ranging from –1 to INT_MAX

Default value: 500

llvm_compile_time_limit

Parameter description: If the percentage of the LLVM compilation time to the executor running time exceeds the threshold specified by llvm_compile_time_limit, an alarm is generated. (To allow the alarm to be generated, execute SET analysis_options="on(LLVM_COMPILE)" before explain performance is executed.) This parameter is supported only by clusters of version 8.3.0 or later.

Type: USERSET

Value range: a floating point number ranging from 0.0 to 1.0

Default value: 0.2

enable_constraint_optimization

Parameter description: Specifies whether the informational constraint optimization execution plan can be used for an HDFS foreign table.

Type: SUSET

Value range: Boolean

• on indicates the plan can be used.
• off indicates the plan cannot be used.

Default value: on

enable_bloom_filter

Parameter description: Specifies whether the BloomFilter optimization is used.

Type: USERSET

Value range: Boolean

• on indicates the BloomFilter optimization can be used.
• off indicates the BloomFilter optimization cannot be used.

Default value: on

Scenario: If in a HASH JOIN, the thread of the foreign table contains HDFS tables or column-store tables, the Bloom filter is triggered.

Constraints:

1. Only INNER JOIN, SEMI JOIN, RIGHT JOIN, RIGHT SEMI JOIN, RIGHT ANTI JOIN and RIGHT ANTI FULL JOIN are supported.
2. JOIN condition of the internal table: It cannot be an expression for HDFS internal or foreign tables. It can be an expression for column-store tables, but only at the non-join layer.
3. The join condition of the foreign table must be simple column join.
4. When the join conditions of the internal and foreign tables (HDFS) are both simple column joins, the estimated data that can be removed at the plan layer must be over 1/3.
5. Joined columns cannot contain NULL values.
6. Data type:
   • HDFS internal and foreign tables support SMALLINT, INTEGER, BIGINT, REAL/FLOAT4, DOUBLE PRECISION/FLOAT8, CHAR(n)/CHARACTER(n)/NCHAR(n), VARCHAR(n)/CHARACTER VARYING(n), CLOB and TEXT.
   • Column-store tables support SMALLINT, INTEGER, BIGINT, OID, "char", CHAR(n)/CHARACTER(n)/NCHAR(n), VARCHAR(n)/CHARACTER VARYING(n), NVARCHAR2(n), CLOB, TEXT, DATE, TIME, TIMESTAMP and TIMESTAMPTZ. The collation of the character type must be C.

runtime_filter_type

Parameter description : Specifies the type of runtime filter used, and only takes effect when enable_bloom_filter is enabled. This parameter is supported only by clusters of version 9.1.0.100 or later.

Type: USERSET

Value range: enumerated values

• All indicates that runtime filters in all scenarios are used.
• Topn_filter indicates runtime filters in join scenarios and order by scenarios with limit are used.
• Bloom_filter indicates that only runtime filters in join scenarios are used, and a bloom filter is generated for filtering after meeting certain conditions.
• Min_max indicates that only runtime filters in join scenarios are used and only a min_max filter is generated for filtering.
• None indicates that no runtime filters are used, and only the original bloom filter has filtering effect.

Default value: All

Application scenarios: HASH JOIN of column-store tables with plan types that span across multiple DN threads, and order by plan types with limit for column-store tables.

Constraints:

• The usage restrictions for JOIN scenarios are the same as those for the enable_bloom_filter parameter.
• In the order by scenario with limit, the order by field types only support SMALLINT, INTEGER, BIGINT, "char", CHAR(n)/CHARACTER(n)/NCHAR(n), VARCHAR(n)/CHARACTER VARYING(n), NVARCHAR2(n), TEXT, DATE, TIME, TIMESTAMP, and TIMESTAMPTZ, and the sorting rules for character types must be specified as C.

runtime_filter_ratio

Parameter description: Specifies the threshold for using bloom filter for fine-grained row-level filtering in join scenarios in runtime filter, and only takes effect when runtime_filter_type is set to a value greater than or equal to Bloom_filter. This parameter is supported only by clusters of version 9.1.0.100 or later.

Type: USERSET

Value range: a floating point number ranging from 0.0 to 1.0

Default value: 0.01

• Application scenario: HASH JOIN of column-store tables, where the internal table estimate_join_rows/foreign table estimate_join_rows ≤ runtime_filter_ratio. Fine-grained row-level filtering is only recommended for join scenarios where there is a significant difference in data volume between the internal and foreign tables. Improper runtime_filter_ratio settings may lead to degraded performance in join scenarios.
• Usage restrictions: Fine-grained row-level filtering is only supported for join field types of SMALLINT, INTEGER, BIGINT, and FLOAT.

enable_extrapolation_stats

Parameter description: Specifies whether to use the extrapolation logic based on historical statistics. Using this logic may increase the accuracy of estimation for tables whose statistics have not been collected. However, there is also a possibility that the estimation is too large due to incorrect inference.

Type: USERSET

Value range: Boolean

• on indicates that the extrapolation logic is used for data of DATE type based on historical statistics.
• off indicates that the extrapolation logic is not used for data of DATE type based on historical statistics.

Default value:

• If the current cluster is upgraded from an earlier version to 8.2.0.100, the default value is off to ensure forward compatibility.
• If the cluster version 8.2.0.100 is newly installed, the default value is on.

autoanalyze

Parameter description: Specifies whether to allow automatic statistics collection for a table that has no statistics or a table whose amount of data modification reaches the threshold for triggering ANALYZE when a plan is generated. In this case, AUTOANALYZE cannot be triggered for foreign tables or temporary tables with the ON COMMIT [DELETE ROWS|DROP] option. To collect statistics, you need to manually perform the ANALYZE operation. If an exception occurs in the database during the execution of autoanalyze on a table, after the database is recovered, the system may still prompt you to collect the statistics of the table when you run the statement again. In this case, manually perform the ANALYZE operation on the table to synchronize statistics.

If the amount of data modification reaches the threshold for triggering ANALYZE, the amount of data modification exceeds autovacuum_analyze_threshold + autovacuum_analyze_scale_factor * reltuples. reltuples indicates the estimated number of rows in the table recorded in pg_class.

Type: SUSET

Value range: Boolean

• on indicates that the table statistics are automatically collected.
• off indicates that the table statistics are not automatically collected.

Default value: on

enable_analyze_partition

Parameter description: Specifies whether to support collecting statistics for a specific partition of a table. After enabling this parameter, you can collect statistics for a specific partition using ANALYZE table_name PARTITION ( partition_name ), and when querying data on this partition of the table, the optimizer will choose to use partition statistics.

Type: USERSET

Value range: Boolean

• on indicates supporting collecting statistics for a specific partition of a table.
• off indicates that collecting statistics for a specific partition of a table is not supported.

Default value: off

analyze_use_dn_correlation

Parameter description: Specifies whether CNs use correlation statistics of DNs when executing ANALYZE. This parameter is supported only by clusters of version 9.1.0.100 or later.

Type: USERSET

Value range: Boolean

• on indicates that CNs use correlation statistics of DNs.
• off indicates that CNs do not use correlation statistics of DNs.

Default value: on

analyze_predicate_column_threshold

Parameter description: Specifies whether to enable ANALYZE operations for predicate columns and the minimum number of columns supported. This parameter is supported only by clusters of version 9.1.0.100 or later.

Type: SIGHUP

Value range: an integer ranging from 0 to 10000

• 0 indicates that ANALYZE operations are disabled for predicate columns, and predicate columns and ANALYZE operations will not be collected.
• A value greater than 0 indicates that predicate column collection is enabled, and it only supports tables with a number of columns greater than or equal to this value.

Default value: 10

enable_runtime_analyze_concurrent

Parameter description: Specifies whether to support concurrent RUNTIME ANALYZE operations on a table. This parameter is supported only by clusters of version 9.1.0.100 or later.

Type: USERSET

Value range: Boolean

• on indicates that concurrent operations are supported.
• off indicates that concurrent operations are not supported.

Default value: on

analyze_max_columns_count

Parameter description: Specifies the maximum number of columns supported by ANALYZE. This parameter is supported only by clusters of version 9.1.0.100 or later.

Type: USERSET

Value range: an integer ranging from –1 to 10000

• –1 indicates that the number of columns supported by ANALYZE is not limited.
• A value greater than –1 indicates that only columns up to this value will be collected, and any columns beyond this value will not be collected.

Default value: –1

query_dop

Parameter description: Specifies the user-defined degree of parallelism.

Type: USERSET

Value range: an integer ranging from –64 to 64.

[1, 64]: Fixed SMP is enabled, and the system will use the specified degree.

0: SMP adaptation function is enabled. The system dynamically selects the optimal parallelism degree [1,8] (x86 platforms) or [1,64] (Kunpeng platforms) for each query based on the resource usage and query plans.

[–64, –1]: SMP adaptation is enabled, and the system will dynamically select a degree from the limited range.

• For TP services that mainly involve short queries, if services cannot be optimized through lightweight CNs or statement delivery, it will take a long time to generate an SMP plan. You are advised to set query_dop to 1. For AP services with complex statements, you are advised to set query_dop to 0.
• After enabling concurrent queries, ensure you have sufficient CPU, memory, network, and I/O resources to achieve the optimal performance.
• To prevent performance deterioration caused by an overly large value of query_dop, the system calculates the maximum number of available CPU cores for a DN and uses the number as the upper limit for this parameter. If the value of query_dop is greater than 4 and also the upper limit, the system resets query_dop to the upper limit.

Default value: 1

query_dop_ratio

Parameter description: Specifies the DOP multiple used to adjust the optimal DOP preset in the system when query_dop is set to 0. That is, DOP = Preset DOP x query_dop_ratio (ranging from 1 to 64). If this parameter is set to 1, the DOP cannot be adjusted.

Type: USERSET

Value range: a floating point number ranging from 0 to 64

Default value: 1

debug_group_dop

Parameter description: Specifies the unified DOP parallelism degree allocated to the groups that use the Stream operator as the vertex in the generated execution plan when the value of query_dop is 0. This parameter is used to manually specify the DOP for specific groups for performance optimization. Its format is G1,D1,G2,D2,...,, where G1 and G2 indicate the group IDs that can be obtained from logs and D1 and D2 indicate the specified DOP values and can be any positive integers.

Type: USERSET

Value range: a string

Default value: empty

This parameter is used only for internal optimization and cannot be set. You are advised to use the default value.

enable_analyze_check

Parameter description: Checks whether statistics were collected about tables whose reltuples and relpages are shown as 0 in pg_class during plan generation. This parameter has been discarded in clusters of version 8.1.3 or later, but is reserved for compatibility with earlier versions. The setting of this parameter does not take effect.

Type: SUSET

Value range: Boolean

• on enables the check.
• off disables the check.

Default value: on

enable_sonic_hashagg

Parameter description: Specifies whether to use the Hash Agg operator for column-oriented hash table design when certain constraints are met.

Type: USERSET

Value range: Boolean

• on indicates that the Hash Agg operator is used for column-oriented hash table design when certain constraints are met.
• off indicates that the Hash Agg operator is not used for column-oriented hash table design.

• If enable_sonic_hashagg is enabled and certain constraints are met, the Hash Agg operator will be used for column-oriented hash table design, and the memory usage of the operator can be reduced. However, in scenarios where the code generation technology (enabled by enable_codegen) can significantly improve performance, the performance of the operator may deteriorate.
• If enable_sonic_hashagg is set to on, when certain constraints are met, the hash aggregation operator designed for column-oriented hash tables is used and its name is displayed as Sonic Hash Aggregation in the output of the Explain Analyze/Performance operation. When the constraints are not met, the operator name is displayed as Hash Aggregation.

Default value: on

enable_sonic_hashjoin

Parameter description: Specifies whether to use the Hash Join operator for column-oriented hash table design when certain constraints are met.

Type: USERSET

Value range: Boolean

• on indicates that the Hash Join operator is used for column-oriented hash table design when certain constraints are met.
• off indicates that the Hash Join operator is not used for column-oriented hash table design.

• Currently, the parameter can be used only for Inner Join.
• If enable_sonic_hashjoin is enabled, the memory usage of the Hash Inner operator can be reduced. However, in scenarios where the code generation technology can significantly improve performance, the performance of the operator may deteriorate.
• If enable_sonic_hashjoin is set to on, when certain constraints are met, the hash join operator designed for column-oriented hash tables is used and its name is displayed as Sonic Hash Join in the output of the Explain Analyze/Performance operation. When the constraints are not met, the operator name is displayed as Hash Join.

Default value: on

enable_sonic_optspill

Parameter description: Specifies whether to optimize the number of hash join or hash agg files spilled to disks in the sonic scenario. This parameter takes effect only when enable_sonic_hashjoin or enable_sonic_hashagg is enabled.

Type: USERSET

Value range: Boolean

• on indicates that the number of files spilled to disks is optimized.
• off indicates that the number of files spilled to disks is not optimized.

For the hash join or hash agg operator that meets the sonic criteria, if this parameter is set to off, one file is spilled to disks for each column. If this parameter is set to on and the data types of different columns are similar, only one file (a maximum of five files) will be spilled to disks.

Default value: on

expand_hashtable_ratio

Parameter description: Specifies the expansion ratio used to resize the hash table during the execution of the Hash Agg and Hash Join operators.

Type: USERSET

Value range: a floating point number of 0 or ranging from 0.5 to 10

• Value 0 indicates that the hash table is adaptively expanded based on the current memory size.
• The value ranging from 0.5 to 10 indicates the multiple used to expand the hash table. Generally, a larger hash table delivers better performance but occupies more memory space. If the memory space is insufficient, data may be spilled to disks in advance, causing performance deterioration.

Default value: 0

plan_cache_mode

Parameter description: Specifies the policy for generating an execution plan in the prepare statement.

Type: USERSET

Value range: enumerated values

• auto indicates that the custom plan or generic plan is selected by default.
• force_generic_plan indicates that the generic plan is forcibly used.
• force_custom_plan indicates that the custom plan is forcibly used.

• This parameter is valid only for the prepare statement. It is used when the parameterized field in the prepare statement has severe data skew.
• custom plan is a plan generated after you run a prepare statement where parameters in the execute statement is embedded in the prepare statement. The custom plan generates a plan based on specific parameters in the execute statement. This scheme generates a preferred plan based on specific parameters each time and has good execution performance. The disadvantage is that the plan needs to be regenerated before each execution, resulting in a large amount of repeated optimizer overhead.
• generic plan is a plan generated for the prepare statement. The plan policy binds parameters to the plan when you run the execute statement and execute the plan. The advantage of this solution is that repeated optimizer overheads can be avoided in each execution. The disadvantage is that the plan may not be optimal when data skew occurs for the bound parameter field. When some bound parameters are used, the plan execution performance is poor.

Default value: auto

wlm_query_accelerate

Parameter description: Specifies whether the query needs to be accelerated when short query acceleration is enabled.

Type: USERSET

Value range: an integer ranging from –1 to 1

• –1: indicates that short queries are controlled by the fast lane, and the long queries are controlled by the slow lane.
• 0: indicates that queries are not accelerated. Both short and long queries are controlled by the slow lane.
• 1: indicates that queries are accelerated. Both short queries and long queries are controlled by the fast lane.

Default value: –1

show_unshippable_warning

Parameter description: Specifies whether to print the alarm for the statement pushdown failure to the client.

Type: USERSET

Value range: Boolean

• on: Records the reason why the statement cannot be pushed down in a WARNING log and prints the log to the client.
• off: Logs the reason why the statement cannot be pushed down only.

Default value: off

hashjoin_spill_strategy

Parameter description: specifies the hash join policy for spilling data to disks. This feature is supported in 8.1.2 or later.

Type: USERSET

Value range: The value is an integer ranging from 0 to 6.

• 0: If an inner table is too large to be fully stored in database memory, the table will be partitioned. If the table cannot be further partitioned and there is not enough memory for storing it, the system will check whether the foreign table can be stored in memory and be used to create a hash table. If the foreign table can be stored in the memory and used to create a hash table, HashJoin will be performed. Otherwise, NestLoop will be performed.
• 1: If an inner table is too large to be fully stored in database memory, the table will be partitioned. If the table cannot be further partitioned and there is still not enough memory for storing it, the system will check whether the foreign table can be stored in memory and be used to create a hash table. If both the inner and outer tables are large, a hash join is forcibly performed.
• 2: If the size of the inner table is large and cannot be partitioned after data is spilled to disks for multiple times, HashJoin will be forcibly performed.
• 3: If the size of the inner table is large and cannot be partitioned after data is spilled to disks for multiple times, the system attempts to place the outer table in the available memory of the database to create a hash table. If both the inner and outer tables are large, an error is reported.
• 4: If the size of the inner table is large and cannot be partitioned after data is spilled to disks for multiple times, an error is reported.
• 5: If the inner table is large and cannot be fully stored in database memory, and the foreign table can be fully stored in memory, the foreign table will be used to create a hash table and perform HashJoin. If the foreign table cannot be fully stored in memory, it will be partitioned until the inner and foreign tables cannot be further partitioned. Then, NestLoop will be performed.
• 6: If the inner table is large and cannot be fully stored in database memory, and the foreign table can be fully stored in memory, the foreign table will be used to create a hash table and perform HashJoin. If the foreign table cannot be fully stored in memory, it will be partitioned until the inner and foreign tables cannot be further partitioned. Then, HashJoin will be forcibly performed.

• This parameter is valid only for a vectorized hash join operator.
• If the number of distinct values is small and the data volume is large, data may fail to be flushed to disks. As a result, the memory usage is too high and the memory is out of control. If this parameter is set to 0, the system attempts to swap the inner and outer tables or perform a nested loop join to prevent this problem. However, a nested loop join may deteriorate performance in some scenarios. In this case, this parameter can be set to 1, 2, or 6 to forcibly perform HashJoin.
• The value 0 does not take effect for a vectorized full join, and the behavior is the same as that of the value 1. The system attempts to create a hash table only for the outer table and does not perform a nested loop join.
• If the inner table is too large to be fully stored in memory, but the foreign table can be stored in memory, you are advised to set this parameter to 5 or 6 rather than 0 or 1, directly performing Hashjoin on the foreign table without multiple rounds of partitioning and spill to disk. If a foreign table contains only a small amount of distinct data, creating a hash table using the foreign table may cause performance deterioration. In this case, you can change the value of this parameter to 0 or 1.

Default value: 0

max_streams_per_query

Parameter description: Controls the number of Stream nodes in a query plan. (This parameter is supported only in 8.1.1 and later cluster versions.)

Type: SUSET

Value range: an integer ranging from –1 to 10000.

• –1 indicates that the number of Stream nodes in the query plan is not limited.
• A value within the range 0 to 10000 indicates that when the number of Stream nodes in the query plan exceeds the specified value, an error is reported and the query plan will not be executed.

• This parameter controls only the Stream nodes on DNs and does not control the Gather nodes on the CN.
• This parameter does not affect the EXPLAIN query plan, but affects EXPLAIN ANALYZE and EXPLAIN PERFORMANCE.

Default value: –1

enable_agg_limit_opt

Parameter description: Specifies whether to optimize select distinct col from table limit N. This parameter is valid only if N is less than 16,384. The parameter table indicates a column-store table. This parameter is supported only by clusters of version 8.2.0.101 or later.

Type: USERSET

Value range: Boolean

• on indicates that the optimization is enabled. After this function is enabled, query results are from different DNs, and you do not need to create a full hash table on each DN, significantly improving query performance.

• off indicates that the optimization is disabled.

Default value: on

stream_ctescan_pred_threshold

Parameter description: minimum number of filter criteria contained in a CTE when enable_stream_ctescan is set to on and the CTE contains only a single table filtering condition. If the value is greater than or equal to the value of this parameter, the share scan mode is used. If the value is less than the value of this parameter, the inline mode is used. This parameter is supported only by clusters of version 8.2.1 or later.

Type: SUSET

Value range: an integer ranging from 0 to INT_MAX

Default value: 2

stream_ctescan_max_estimate_mem

Parameter description: maximum estimated memory value of the CTE when enable_stream_ctescan is set to on. This parameter must be used together with stream_ctescan_refcount_threshold. If the estimated memory is greater than the value of stream_ctescan_max_estimate_mem and the number of references is less than the value of stream_ctescan_refcount_threshold, the inline mode is used. Otherwise, the sharescan mode is used. This parameter is supported only by clusters of version 8.2.1 or later.

Type: SUSET

Value range: an integer ranging from 32 x 1024 (32 MB) to INT_MAX, in KB.

Default value: 256 MB

stream_ctescan_refcount_threshold

Parameter description: maximum number of times that the CTE can be referenced when enable_stream_ctescan is set to on. This parameter must be used together with stream_ctescan_max_estimate_mem. If the estimated memory is greater than the value of stream_ctescan_max_estimate_mem and the number of references is less than the value of stream_ctescan_refcount_threshold, the inline mode is used. Otherwise, the sharescan mode is used. This parameter is supported only by clusters of version 8.2.1 or later.

Type: SUSET

Value range: an integer ranging from 0 to INT_MAX

Default value: 4

This parameter takes effect only when the value is greater than 0. When the value is 0, only stream_ctescan_max_estimate_mem is used to control the inline behavior.

inlist_rough_check_threshold

Parameter description: Specifies the maximum number of values in the IN condition when enable_csqual_pushdown is enabled and the filter criterion is IN for rough check pushdown. If the number of values in the IN filter condition exceeds the value of this parameter, the maximum and minimum values in the IN filter condition are used for pushdown. This parameter is supported only by clusters of version 8.2.0.101 or later.

Type: SUSET

Value range: an integer ranging from 0 to 10000

Default value: 100

If the IN condition is executed on the only distribution column of a table, values can be filtered on DNs. In this case, the maximum number of values in the IN condition is inlist_rough_check_threshold multiplied by the number of DNs.

enable_array_optimization

Parameter description: whether to split the Array type generated by the IN, ANY, or ALL condition into common expressions for execution. This parameter will support multiple optimizations such as vectorized execution, rough check pruning, and partition pruning. This parameter is supported only by clusters of version 8.2.1 or later.

Type: SUSET

Value range: Boolean

• on indicates that expressions of the Array type are split for optimization.
• off indicates that expressions of the Array type are not split for optimization.

Default value: on

max_skew_num

Parameter description: controls the number of skew values allowed by the optimizer for redistribution optimization. This parameter is supported only by clusters of version 8.2.1 or later.

Type: SUSET

Value range: an integer ranging from 0 to INT_MAX

Default value: 10

enable_dict_plan

Parameter description: Specifies whether the optimizer uses dictionary encoding to speed up queries that use perators such as Group By and Filter. This parameter is supported only by clusters of 8.3.0 or later.

Type: USERSET

Value range: Boolean

• on: enables the optimizer dictionary encoding.
• off: disables the optimizer dictionary encoding.

Default value: off

dict_plan_distinct_limit

Parameter description: Specifies a distinct value threshold for a column. Dictionary encoding is enabled only when the distinct values of the column no more than the value of this parameter. This parameter is supported only by clusters of 8.3.0 or later.

Type: USERSET

Value range: 0 to INT_MAX

Default value: 10000.

The two parameters dict_plan_distinct_limit and dict_plan_duplicate_ratio determine if dictionary encoding is applied.

dict_plan_duplicate_ratio

Parameter description: Specifies the repetition rate threshold of a column. Dictionary encoding is enabled only when the repetition rate of the column is greater than or equal to the threshold. Dictionary encoding is suitable for columns with a small number of distinct values and a high repetition rate. This parameter is supported only by clusters of 8.3.0 or later.

Type: USERSET

Value range: 0.0 to 100, in percentage

Default value: 90

The two parameters dict_plan_distinct_limit and dict_plan_duplicate_ratio determine if dictionary encoding is applied.

enable_cu_predicate_pushdown

Parameter description: Specifies whether simple filter criteria are pushed down to the CU for filtering. This parameter is supported only by clusters of 8.3.0 or later.

Type: USERSET

Value range: Boolean

• on: Simple filter criteria are pushed down to the CU for filtering.
• off: Simple filter criteria are not pushed down to the CU for filtering.

Default value: off

Simple filter criteria in dictionary columns refer to expressions containing the equal sign (=), IN, and is (not) null. Before the CU loads VectorBatch, this filter condition is applied at the storage layer. Therefore, this filter is called CU Predicate Filter.